Strategic Approach: CPS-HSPR
Master Sample Listing Phase
06/11/2024
Introduction and Purpose
- Duration: 01 April to 30 June 2025 (90 days)
- Scope: 468 Primary Sampling Units (PSUs)
across 7 districts
- Objective: Comprehensive master sample
frame preparation
- Importance: Accurate sampling frame for
future surveys and analyses
Project Overview
-Districts: Metro1, Metro2, Cape Winelands,
Central Karoo, Garden Route, Overberg, West
Coast
- Teams: 9 teams across the province
- Total Listers: 25 across all districts, 35
- Workload: 468 PSUs, 126 PSUs per week
National Training , 09-13 December 2024
Resource Deployment
- 25 listers using GPS-enabled tablets
Logistics: Vehicles allocated based on terrain
and PSU dispersion
Provincial Major stakeholders DSC, GA,Sos,
DM, PM,GIS,Marketing etc….
Provincial Sample
Metro1 & 2
Overview Provincial Sample
Overview
Project Period: 01 March 2025 to 31 May 2025 (90 days).
Total Workload: 468 PSUs.
Districts Covered: 7 districts (Metro1, Metro2, Cape Winelands, Central
Karoo, Garden Route, Overberg, West Coast).
Total Listers Required: 25 , 32 Overtraining, listers across all districts.
Sample Size Distribution (Districts)
Overview
Project Period: 01 March 2025 to 31 May 2025 (90 days).
Total Workload: 468 PSUs.
Districts Covered: 7 districts (Metro1, Metro2, Cape Winelands, Central
Karoo, Garden Route, Overberg, West Coast).
Total Listers Required: 25 listers across all districts. 35 to be trained
Plan being develpped divides the workload proportionally across teams,
ensuring consistency in daily and weekly targets while factoring in the
available human and logistical resources.
Metro
Sample Size
Spatial
DIstribution
Metro1=74
Metro2=82
Metro Sample
Size Spatial with
LPOs
Metro1=74
Metro2=82
Size Spatial with
LPOs
Metro1=74
Metro2=82
CMHTI Complexes
Estates
https://geoserverspatialdata.github.io/d
atataanalysisprovincially/
https://geoserverspatialdata.github.io/s
amplespatialdist/
Key Recommendations
- Maintain flexibility for unexpected
disruptions
- Use a centralized monitoring system
- Optimize resource deployment in challenging
districts
- Strengthen QA sampling and analysis
- Incorporate technology like GPS-enabled
devices for accuracy
Conclusion
- Equitable workload distribution ensures
sustainability
- Structured targets maintain uniform
productivity
- QA processes guarantee high-quality data
- Flexibility and real-time monitoring enable
timely completion